Mixed Ramp-Gaussian Basis Sets for Core-Dependent Properties: STO-RG and STO-R2G for Li-Ne

作者
Claudia S. Cox,Juan C. Zapata Trujillo,L. K. McKemmish
出处
期刊:Australian Journal of Chemistry [CSIRO Publishing]
卷期号:73 (10): 911-922 被引量:4
标识
DOI:10.1071/ch19466
摘要

The traditional Gaussian basis sets used in modern quantum chemistry lack an electron-nuclear cusp, and hence struggle to accurately describe core electron properties. A recently introduced novel type of basis set, mixed ramp-Gaussians, introduce a new primitive function called a ramp function which addresses this issue. This paper introduces three new mixed ramp-Gaussian basis sets - STO-R, STO-RG and STO-R2G, made from a linear combination of ramp and Gaussian primitive functions - which are derived from the single-core-zeta Slater basis sets for the elements Li to Ne. This derivation is done in an analogous fashion to the famous STO-nG basis sets. The STO-RG basis functions are found to outperform the STO-3G basis functions and STO-R2G outperforms STO-6G, both in terms of wavefunction fit and other key quantities such as the one-electron energy and the electron-nuclear cusp. The second part of this paper performs preliminary investigations into how standard all-Gaussian basis sets can be converted to ramp-Gaussian basis sets through modifying the core basis functions. Using a test case of the 6-31G basis set for carbon, we determined that the second Gaussian primitive is less important when fitting a ramp-Gaussian core basis function directly to an all-Gaussian core basis function than when fitting to a Slater basis function. Further, we identified the basis sets that are single-core-zeta and thus should be most straightforward to convert to mixed ramp-Gaussian basis sets in the future.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
玄博元完成签到,获得积分10
1秒前
2秒前
kktwo应助小小鸟采纳,获得10
3秒前
张欢馨应助小小鸟采纳,获得10
3秒前
走走发布了新的文献求助10
5秒前
慕青应助喽喽采纳,获得10
5秒前
kento驳回了七听应助
6秒前
7秒前
李健应助东风采纳,获得10
7秒前
优秀夏天发布了新的文献求助10
9秒前
10秒前
思源应助球球采纳,获得10
10秒前
11秒前
传奇3应助阿羡采纳,获得10
11秒前
onlyone发布了新的文献求助10
12秒前
12秒前
黄药师完成签到,获得积分10
13秒前
13秒前
14秒前
药膳干发布了新的文献求助10
14秒前
16秒前
zoey发布了新的文献求助10
17秒前
17秒前
17秒前
核桃发布了新的文献求助10
18秒前
越凡发布了新的文献求助10
18秒前
科研通AI6.2应助杜欢采纳,获得10
19秒前
JL发布了新的文献求助10
19秒前
19秒前
21秒前
呼啦啦树獭完成签到,获得积分10
21秒前
22秒前
球球完成签到,获得积分10
24秒前
25秒前
听说你还在搞什么原创完成签到 ,获得积分10
26秒前
26秒前
华仔应助Sthwrong采纳,获得10
27秒前
clyhg完成签到,获得积分10
27秒前
zoey完成签到,获得积分10
30秒前
乐乐应助受伤11采纳,获得10
30秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Reducing Compassion Fatigue, Secondary Traumatic Stress and Burnout 600
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Mammalian Synthetic Biology 500
Auslegungsgeschichte 500
Cosmos as Art Object: Studies in Plato's Timaeus and Other Dialogues 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7638018
求助须知:如何正确求助?哪些是违规求助? 9211365
关于积分的说明 19758586
捐赠科研通 7204977
什么是DOI,文献DOI怎么找? 3275778
关于科研通互助平台的介绍 2437385
邀请新用户注册赠送积分活动 2272936